Identification of N4-Acetylcytidine-Related Biomarkers in Adult Asthma: An Integrative Multi-Omics Study

Adult asthma (AA) is a chronic respiratory disease that significantly affects morbidity and quality of life. N4-acetylcytidine (ac4C) might have a crucial part in facilitating the occurrence and development of inflammatory diseases. The objective of this research was to find biomarkers associated with ac4C in AA, potentially paving the way for targeted therapies.

The data of AA were procured from a public database, and ac4C-related genes (ac4CRGs) were downloaded from the literature. Candidate genes were obtained by overlapping the results of differentially expressed genes (DEGs) and ac4CRGs. We conducted two-sample Mendelian randomization (MR) analysis with ac4C-related candidate genes as exposures and adult asthma as the outcome; instrumental variables were selected from genome-wide association study (GWAS) data, and causal associations were validated via inverse variance weighted (IVW), MR-Egger, weighted median and other MR methods, with heterogeneity and horizontal pleiotropy tested to guarantee the reliability of causal inferences. The identification of biomarkers was facilitated by Mendelian randomization (MR), machine learning, receiver operating characteristic (ROC) curve, and gene expression analyses. Of great significance was the employment of the nomogram to assess the diagnostic effectiveness of the biomarkers. Following this, immune infiltration and drug prediction analyses were performed. Single-cell analysis was performed to acquire cell types and identify key cells by biomarker expression. Ultimately, in vitro, reverse transcription quantitative polymerase chain reaction (RT-qPCR) was utilized to measure the expression levels of biomarkers.

MR analysis verified that MCM5, TRIP6 and PALM were protective factors for AA (OR<1, P<0.05), while PUM1 and NPEPL1 were risk factors (OR>1, P<0.05). MCM5, PUM1, TRIP6, PALM, and NPEPL1 were identified as biomarkers. The nomogram developed utilizing these biomarkers demonstrated a satisfactory capacity for differentiating among various sample types. Moreover, MCM5 demonstrated substantial positive correlation with B cells and CD8 T cells (r > 0.30, P < 0.05). Furthermore, valproic acid simultaneously affected the 3 biomarkers PUM1, TRIP6, and NPEPL1. Single-cell analysis revealed that alveolar epithelial cells and mononuclear macrophages were considered key cell types that played a critical role in AA. A marked decrease in the levels of the 5 biomarkers were observed in the asthma mice samples as compared to the control mice samples.

This study preliminary identified MCM5, PUM1, TRIP6, PALM, and NPEPL1 as biomarkers for AA, offering valuable insights that could provide preliminary clues for future mechanistic and therapeutic studies.